Abstract:
When performing sparse matrix factorization, the ordering of matrix rows and columns has a dramatic impact on the factorization time. This paper describes an approach to the reordering problem that produces significantly better orderings than previous methods. The algorithm is a hybrid of nested dissection and minimum degree ordering, and combines an assortment of algorithmic techniques.